Generative AI is quickly becoming a default part of the software development lifecycle. Faster delivery can also increase security risk, operational fragility, and decisions that are difficult to review or audit after the fact.
This session focuses on AI coding guardrails: practical, developer-friendly controls that help teams adopt coding assistants with confidence while maintaining strong security, governance, and assurance. We will walk through four maturity levels for agentic coding controls.
Level 1 uses built-in steering mechanisms in modern agentic IDEs, including project context files, rules, and instruction layers. These establish consistent expectations for architecture, security patterns, data handling, logging, and “how we do things here,” so teams reduce variability and improve repeatability.
Level 2 adds context-injection agents that deliver guidance at the right time. They provide the relevant requirements, approved patterns, and constraints based on what is changing, the type of work underway, and where the developer is in the workflow.
Level 3 adds deterministic, policy-as-code guardrails in pull requests and CI/CD to enforce security, quality, and compliance requirements with measurable outcomes and audit-ready evidence.
Finally, we hit level 4, where everything implemented in levels 1 through 4 continuously improves to strengthen controls over time.
